Smart and Aware Pervasive Healthcare Environmentubimon.doc.ic.ac.uk/saphe/public/eopmtg/GZY_saphe......
Transcript of Smart and Aware Pervasive Healthcare Environmentubimon.doc.ic.ac.uk/saphe/public/eopmtg/GZY_saphe......
www.saphe.infoSupported by DTI Technology Programme
SAPHESmart and Aware Pervasive Healthcare
Environment
Guang-Zhong Yang, Imperial College London
Technical Objectives
• Miniaturised sensing with self-management and configuration
• Local data abstraction and sensor fusion/inferencing with low power sensor and wireless data path
• Processing-on-node technology for context aware sensing
• Automated trust-based decision support and "affective computing" for improved human-computer interfacing
• Intelligent trend analysis and large scale data mining
Project Overview
• To develop a novel architecture for unobtrusive pervasive sensing to link physiological/metabolic parameters and lifestylepatterns for improved well-being monitoring and early detection of changes in disease.
By sensing under normal physiological conditionscombined with intelligent trend analysis, SAPHE opens up new opportunities for the UK ICT and healthcare sectors in meeting the challenges of demographic changes associated with the aging population
DTI Technology Programme
Evolution of Computer TechnologiesMoore's Law
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1971 1976 1981 1986 1991 1996 2003
Year
Tran
sist
ors
(log)
Estimate Actual
40044-bit108kHz0.06MIPS2.3K transistors1971
8008108kHz8-bit16kB0.06MIPS3.5K transistors1972
80808-bit2Mhz0.64MIPS6k transistors1974
808616-bit8MHz0.8MIPS29K transistors1978
8028616-bit12MHz2.7MIPS134K transistors1982
8038632-bit20MHz6MIPS275K transistors1985
8048625MHz20MIPS1.2M transistors1989
Pentium32-bit66MHz100MIPS 3.2M transistors1993
Pentium II233MHz300MIPS7.5M transistors1997
Pentium III450-500MHz510MIPS9.5M transistors1999
Pentium 41.4&1.5GHz1.7GIPS42M transistors2000
Pentium M600Mhz-1.6GHz6.5GIPS77M transistors2003
P4 Prescott2.8-3.4 GHz125M transistors7GIPS2004
Pentium D3.2 GHz15GIPS230M transistors2005
40048008 8080 8086
8028680386 80486
Pentium Pentium IIPentium III
Pentium 4Pentium M
P4 PrescottPentium D
http://www.granneman.com/http://velox.stanford.edu/group/chips_micropro_body.html
http://home.datacomm.ch/fmeyer/cpu/http://www.pc-erfahrung.de/Index.html?ProzessormodelleIntelItanium2.html
http://www.pc-erfahrung.de/
http://trillian.randomstuff.org.uk/~stephen/history
http://www.theregister.co.uk/2004/02/02/intel_prescott_90nm_pentium/http://www.intel.com/products/processor/pentiumm/image.htm
Evolution of Computer Technologies
Bell’s Law
New computing class every decadeNew applications and contents develop around each new class
year
log
(peo
ple
per c
ompu
ter/p
rice)
Mote Evolution
Biosensor Design
Biocompatibility & Materials
Wireless Communication
Low Power Design &
Scavenging
Autonomic Sensing
Standards & Integration
BSN
Wh
at d
oes
BSN
Cov
er?
Biosensor Design
Implant blood pressureflow sensor (CardioMEMS)
Glucose sensor(Glucowatch)
Thermistor(ACR system)
Implant ECG recorder(Medtronics –Reveal)
Oxymeter(Advanced Micronics)
Implant pH sensor(Metronics – Bravo)
Pill-sized camera(Given Imaging)
Thermistor
ECG
SpO2
Glucose concentration
Blood pressure
pH measurement
Capsule endoscopy
MEMS - Microelectromechanical System
Integrated micro devices or systems combining electrical and mechanical components
Fabricated using integrated circuit (IC) batch processing techniques
Size range from micrometers to millimetres
Applications includes: accelerometers, pressure, chemical and flow sensors, micro-optics, optical scanners, and fluid pumps
Tactile Sensor for Endoscopic Surgery(SFU)
Pressure Sensor for Clinical Use(SFU)
CMOS Micromachined Flow Sensor(SFU)
Biocompatibility and Materials
Biosensors
Stents
Tissue Engineering
Pattern and manipulate cells in micro-array format
Drug delivery systems
Carol Ezzell Webb, “Chip Shots”, IEEE Spectrum Oct 2004
Smart Pill – Sun-Sentinel Co.
Implant blood pressureflow sensor (CardioMEMS)
Drug releasing stents -Taxus stents - Boston Scientific Co.
Ozkan et. al (2003), Langmuir
Power Scavenging
Photovoltaics (Solar cells)
15-20% efficiency (single crystal silicon solar cell)15mW/cm2 (midday outdoor) to 10µW/cm2 (indoors)
Temperature Gradients
1.6% efficiency (at 5oC above room temperature)40 µW/cm2 (5oC differential, 0.5cm2, and 1V output)
Human Power
Human body burns 10.5MJ/day (average power dissipation of 121W)330 µW/cm2 (piezoelectric shoe)
Wind/Air Flow
20-40% efficiency (windmills, with wind velocity 18mph)
Vibrations
Electromagnetic, electrostatic, and piezoelectric devices 200 µW (1cm3 power converter with vibration of 2.25 m/s2 at 120Hz)
Nuclear microbatteries
With 10 milligrams of polonium-210, it can produce 50mW for more than 4 months
It can safely be contained by simple plastic package, as Nickel-63 or tritium can penetrate no more than 25 mm
Panasonic BP-243318
Applied Digital Solutions –thermoelectric generator
MIT Media Lab
MIT – MEMS piezoelectric generator
Cornell University - Nuclear micro-generator (with a processor and a photo sensor)
Trust, Security
and Policy
Self-configuration, healing,
managing of software components
Network Storage
and Decision Support Agents
Multi-sensor Analysis
and Fusion
Environment Sensors and
Context
Screening Diagnosis & Staging
Treatment & Monitoring
Follow-up
GeneticPredisposition
DNAmutation
DevelopingMolecular signature
Firstsymptoms
Progressingdisease
Unspecific markersPOC imagingMammography
Diagnostic imagingBiopsies
SurgeryCath labRadiation therapy
Diagnostic imagingUnspecific markerTo
day
Screening Diagnosis & Staging
Treatment & Monitoring
Follow-up
Specific markers(MDx)
Molecular imagingQuantitative imagingWhole-body imagingComp Aided Diagn.
Min invasive surgeryLocal/targeted drugDeliveryDrug trackingTissue analysis (MDx)
Non-invasive and quantitative imagingMolecular imagingMolecular diagnostics (MDx)
Tom
orro
w
Driver 1: The Aging Population
The proportion of elderly people is likely to double from 10% to20% over the next 50 years.
In the western world, the ratio of workers to retirees is declining.
The number of people living alone is rising.
A change of care provision is needed for these patients.
Driver 2: Chronic Disease
Ischemic heart disease
Hypertension
Diabetes
Neuro-degenerative disease (Parkinsons, Alzheimers)
Global deterioration (Dementias)
Acute presentations
Interventions
Post elective care
Post-operative monitoring
Driver 3: Acute Disease
Special Tests
Imaging
Peak Flow
ECGBlood Tests
O2 Sats
Blood Pressure
Medical Records
Exam
History
Patient
Only a SNAPSHOT of a patient’s health
Driver 4: Diagnostics
BSN for HealthcareDynamic
Continuous use 24/7
Preventative
Earlier diagnosis
Home-based
Post-operative monitoring
Unobtrusive
Minimal interventions
Improving Quality-of-Life
Anytime
Anywhere
Anybody
The Ageing Body
Brain and nervous system
Circulatory system
Musculoskeletal system
Respiratory system
Visual and sensory systems
Special Tests
Imaging
Peak Flow
ECGBlood Tests
O2 Sats
Blood Pressure
Medical Records
Exam
History
Patient
Only a SNAPSHOT of a patient’s health
Driver 4: Diagnostics
Wearable
Ambi
ent
Intelligent
MSN
MSN
MSN
MSN
MSN
ASN WSHWSH
WSH
WSH
WSH
WiBroCDMA 2000802.11 (WLAN)802.20 (MBWA)
802.16e (WiMAX)HSDPA/HSUPALTE-UMTS
BSN
WiBroCDMA 2000802.11 (WLAN)802.20 (MBWA)
802.16e (WiMAX)HSDPA/HSUPALTE-UMTS
Door sensors
Sensing Development
SAPHE eAR sensor
SAPHE low power radio module
SAPHE environmental Blob sensor
PIR sensors
CardioneticsECG
SAPHE mobile hub
e-AR Sensore-AR: How does it work?
Tiny vestibular organ
3 semicircular canals or hollow tubes
Each tube detects the 3 different motions: pitch (x), roll (y) and yaw (z)
Each tube filled with liquid, and the tube contains millions of microscopic hairs
z
xyAccelerometer
Initial contact
Running Gait
Stance phase reversal
Toe off Swing phase reverse
Initial contact
Forc
e
Time (s)0 0.1 0.2
Impact peak-the impact (shock) of the foot to the ground
Propulsion peak – propulsion of body forward (i.e. marking the end of deceleration and the beginning of acceleration)
e-AR Ground Reaction Force
FFT of Walking when Recovered
1 51 101 151 201 251 301 351 401 451 501
e-AR Sensor and Ankle injury
Accelerometer readings of the subject were recorded before and after the injury, and when the subject is fully recovered
Distinctive patterns were found when the subject was suffering from the ankle injury
FFT of Normal Walking
1 51 101 151 201 251 301 351 401 451 501
FFT of Walking with Leg Injury
1 51 101 151 201 251 301 351 401 451 501
Before Injury After Injury Fully Recovered
FFT
Ankle injury – Cont’d
STSOM – different clusters are formed for the different gait patterns (using features from FFT)
KNN – clusters are formed for different gaits (using features from wavelet transform), and the recognition accuracy is above 90%
Normal gait
Injured gait
Gait abnormalities
Propulsive gait Scissors gait Spastic gait Steppage gait Waddling gait
Typical associated diseases
- Carbon monoxide poisoning
- Manganese poisoning
- Parkinson's disease
- Temporary effects from drugs
- Stroke
- Cervical spondylosiswith myelopathy
- Liver failure
- Multiple sclerosis
- Pernicious anemia
- Spinal cord trauma
- Cerebral palsy
- Brain abscess
- Brain tumor
- Stroke
- Head trauma
- Multiple sclerosis
- Congenital hip dysplasia
- Muscular dystrophy
- Spinal muscle atrophy
- Guillain-Barre syndrome
- Herniated lumbar disk
- Multiple sclerosis
- Peroneal muscle atrophy
- Peroneal nerve trauma
- Poliomyelitis
- Polyneuropathy
- Spinal cord trauma
Clinical Gait Analysis
Benefits to Patients
• Truly pervasive, easy to wear and require minimal user interaction
• Early detection of the onset of the disease to avoid complication
• Used both for disease and well-being monitoring• Smart to wear, multi-function (e.g with integrated music player)
to avoid stigmatising• Sensing under normal physiological conditions• Reconfigurability of the devices means constant improvement
of the system capability • Intelligent ambient sensing can ultimately replace existing
security and monitoring devices, and therefore brings significant cost benefit
Benefits to Health and Care Providers
• Early detection means well informed care activities and improve resource management
• Trend analysis and decision support simplifies care workflow management and decreases (improves) staff/client ratio
• Truly pervasive, easy to install and customisation suggest minimal additional work for system deployment
• Sensing under normal physiological conditions ensures improved patient compliance and acceptance
• Reconfigurability of the devices means the ease of adaptation of the care/monitoring provision as the condition of the patientchanges
• Pooled population data provides evidence based care provision and viable financial planning
www.saphe.infoSupported by DTI Technology Programme